1. Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1: Finnish Meteorological Institute 2: University of Helsinki

2. Presentation outline  A short overview of the current AATSR aerosol algorithm over land  Comparison with the AERONET data  Datasets and the Web page

3. The AATSR Dual View (ADV) algorithm Used to monitor aerosol optical properties over land The algorithm exploits the AATSR measurements made in two viewing angles (nadir and 55° forward ) to exclude the surface contribution from the measured TOA-reflectance. Over ocean a single view algorithm is used The retrieved parameters include aerosol optical depth at 555, 659, and 1600 nm wave lengths, mixing ratio and Ångström coefficient at 1x1 km2 resolution. 55

4. New implementations Modified linear-mixing method After Abdou et al., 1997 To reduce the AOD overestimation by AATSR Interpolation between the AOD levels Several new aerosol models (Dubovik et al. 2002, Levy et al. 2007) Based on AERONET observations (Dubovik et al. 2002, Levy et al. 2007) Current status of the ADV algorithm

5. Aerosol models Fine mode models (r eff ~ 0.1 µm) Sulphate type aerosol Industrial pollution Dirty pollution Coarse mode models (r eff ~1 µm) Neutral Mineral type aerosol In each retrieval two aerosol model are mixed The best mixture for each case (pixel) is found by the least squares method in the iteration procedure.

6. Comparison with the AERONET measurements The goal is to find the most plausible aerosol models for large dataset processing. Available AERONET stations are centered either around Beijing or Shanghai area. large interesting areas remain still uncovered. Studied months (Mar.-Nov. 2008) are selected by the availability of the AERONET-data. Beijing, XiangHe, Xin- glong Hefei, NUIST, Shouxian, Qiandaohu, LA-TM, Hangzhou, and Ningbo

7. 1.5 and 2.0 level AERONET-data is used The monthly number of collocated AATSR and AERONET observations can vary a lot. Since the retrieved AODs can vary depending on which aerosol models are used, the AATSR retrievals for each AERONET station are done with all the possible combinations of the five models.

8. On average the best agreement with the AERONET AOD at the Beijing area was obtained with the combination of industrial or dirty pollution and neutral coarse model aerosol. During the summer months the mixing ratio for fine particles was about 100% best agreement was obtained with a mixture of sulphate and dirty or industrial pollution. the best agreement was obtained with a mixture of sulphate and dirty or industrial pollution.   To some degree the best aerosol model combinations depended on the location (urban, rural) and season and/or the origin of the airflow. AOD 555nm 7.3.2009 Note different scales

9. At Shanghai area the fine mode fraction was near 100% most of the time with the exception of the summer months. During the summer months, the industrial pollution combined with the neutral coarse model was mainly the optimal combination. Hangzhou City 20.5.2008 Qiandaohu 20.5.2008 AOD 555 nm 20.5.2008

10. The AATSR ADV retrieval algorithm works for a wide range of AODs and for different aerosol types.

11. Dust and smog episodes has been shown to be extremely di ffi cult cases for the di ff erent satellite algorithms, also for the AATSR ADV. RGB-compositeBT 11 microns - BT12 microns  The dense dust plume over Beijing (Mar 2008) was almost completely missed by the algorithm.  We are testing alternative methods for detecting dust.  For the smog episodes, the best agreement was obtained with dirty pollution and sulphate aerosol.  The AATSR AOD pattern is correctly retrieved but the absolute values remain underestimated.

12. Based on the results from collocated AATSR-AERONET comparisons, the combination of industrial pollution – neutral coarse mode aerosol was selected to the larger dataset processing.

13. Datasets and Web-page AATSR retrievals over China are produced for Mar-Nov 2008 (dataset 1.0) Figures: AOD at 555 nm with 1x1 km 2 resolution Retrievals for specific AERONET stations as a 25 km x 25 km spatial averages. Web page: http://AATSRaerosol.fmi.fi Web page: http://AATSRaerosol.fmi.fi

15. First 13 letters in the file name refer to the AATSR aerosol model Contents: Aeronet sitename, Year, Month, Day, Hour, Minute AOD 555 nm, std AOD555, AOD 659 nm, std AOD659, AOD 1600 nm, std AOD1600, mixratio1 and std mixratio1 AATSR data is being collected from 25x25 km2 AOD distributions. AATSR data point has to be closer than 12.5 km to an Aeronet site to be accepted. Hangzhou_City 2008 8 14 1 24 0.97303 0.13738 0.67139 0.10494 0.07817 0.03798 0.98758 0.01763 Hangzhou_City 2008 8 17 1 30 2.33027 0.67590 1.62357 0.50255 0.18589 0.09586 1.00000 0.00000 Hangzhou_City 2008 8 27 1 16 0.78876 0.10022 0.54880 0.06865 0.07022 0.02553 0.97778 0.02473 Hefei 2008 8 4 1 38 1.91194 0.43644 1.31999 0.31326 0.14173 0.05517 1.00000 0.00000 Hefei 2008 8 7 1 44 0.53526 0.16173 0.38287 0.12164 0.08605 0.05814 0.98791 0.02038 Hefei 2008 8 23 1 40 1.59965 0.39220 1.09671 0.26171 0.11173 0.03512 1.00000 0.00000 Hefei 2008 8 26 1 46 0.87338 0.13547 0.61559 0.09554 0.10290 0.04321 0.99303 0.01642 LA-TM 2008 8 11 1 18 0.76750 0.40893 0.52600 0.27898 0.05500 0.02947 0.99681 0.01034 LA-TM 2008 8 14 1 24 1.87328 0.69644 1.30007 0.51758 0.13592 0.08705 0.99534 0.00857 LA-TM 2008 8 17 1 30 3.31376 0.45795 2.51738 0.43524 0.40932 0.14193 1.00000 0.00000 LA-TM 2008 8 20 1 35 1.33437 0.78271 0.93298 0.56789 0.13090 0.09137 0.96171 0.04904 Ningbo 2008 8 8 1 13 0.92328 0.37913 0.63798 0.25727 0.08072 0.03460 0.99595 0.00956 Ningbo 2008 8 14 1 24 1.43649 0.15718 0.98724 0.11467 0.10280 0.02894 0.99560 0.00839 Ningbo 2008 8 27 1 16 0.47284 0.04367 0.32331 0.02847 0.03300 0.01033 0.98576 0.02296 Ningbo 2008 8 30 1 21 2.23475 0.60355 1.52544 0.40969 0.13498 0.03032 1.00000 0.00000 Qiandaohu 2008 8 4 1 38 0.60112 0.21101 0.44109 0.17315 0.13379 0.11936 0.88380 0.08165 Qiandaohu 2008 8 20 1 35 0.73438 0.18651 0.54564 0.15619 0.17629 0.11825 0.92748

16. Conclusions The AATSR ADV- algorithm is able to retrieve AODs over China in highly di ff erent situations. Anthropogenic fine mode aerosol components dominate the ADV retrieval. Smog and dust cases are difficult as for all satellite instruments, and lead to underestimation of AATSR AOD. Dataset 1.0 is available at the web-page Figures of the AOD pattern at 555 nm at 1x1 km 2 resolution Data for specific AERONET stations. The dataset is updated regularly Article submitted to Remote Sensing of Environment, AATSR Special Issue